Introducing new multiple expert decision combination topologies: a case study using recognition of handwritten characters

A new topology for classifying decision combinations of multiple experts in the framework of a multiple expert character recognition platform is introduced. It is demonstrated that many existing multiple expert configurations for character recognition can be categorised by using this method of defining classification strategies. It is also demonstrated that the design of multiple expert character recognition configurations can be streamlined by classifying these structures in terms of how the channels used for carrying information among different experts are interconnected irrespective of the algorithms used by cooperating experts and by the final decision combination expert. Case studies of actual multiple expert character recognition configurations have been investigated and it is shown how they can be categorised with respect to the decision combination topologies introduced in the paper